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NumPy Essentials

NumPy Essentials

By : Jaidev Deshpande, Chin, Tanmay Dutta, Shane Holloway
3.3 (3)
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NumPy Essentials

NumPy Essentials

3.3 (3)
By: Jaidev Deshpande, Chin, Tanmay Dutta, Shane Holloway

Overview of this book

In today’s world of science and technology, it’s all about speed and flexibility. When it comes to scientific computing, NumPy tops the list. NumPy gives you both the speed and high productivity you need. This book will walk you through NumPy using clear, step-by-step examples and just the right amount of theory. We will guide you through wider applications of NumPy in scientific computing and will then focus on the fundamentals of NumPy, including array objects, functions, and matrices, each of them explained with practical examples. You will then learn about different NumPy modules while performing mathematical operations such as calculating the Fourier Transform; solving linear systems of equations, interpolation, extrapolation, regression, and curve fitting; and evaluating integrals and derivatives. We will also introduce you to using Cython with NumPy arrays and writing extension modules for NumPy code using the C API. This book will give you exposure to the vast NumPy library and help you build efficient, high-speed programs using a wide range of mathematical features.
Table of Contents (11 chapters)
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Summary


In this chapter, we saw how to covert Python code into Cython. We also looked into some example Python code that involved NumPy arrays. We briefly explained the concept of boxing and unboxing in the Python language and how they affect the performance of code. We also explained how you can explicitly unlock the notorious GIL. To dig further deep in the Cython world, we recommend Learning Cython ProgrammingPhilip HerronPackt Publishing. In the next chapter, you will learn about the NumPy C API and how to use it.

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NumPy Essentials
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